Russian Scientists Learn to Use Brain Signals to Control Computers
13:23 GMT 11.10.2022 (Updated: 13:38 GMT 11.10.2022)
© Center for Public Communications of SFedU
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Scientists from the Southern Federal University (SFedU) have proposed new methods and algorithms for the intelligent analysis of signals of human brain activity. According to their estimates, the developed software complex will allow brain-computer interfaces to be individualized so that unique features of a person can be taken into account.
Brain-computer interfaces are non-muscle control and communication systems designed to help people who have lost mobility and independence. It is not uncommon for such patients, though conscious, to be bedridden because of a loss of muscular activity.
Neural interfaces link neural activity to an external device (for example, a bionic prosthesis), which is controlled by brain signals, literally by “the power of thought”. Scientists from the Southern Federal University (SFedU) in Rostov on Don, set out to decipher the individual characteristics of such signals to apply them in everyday rehabilitation practice. The results of their study were published in peer-reviewed journal Applied Sciences.
“Individual brain characteristics are known to contribute significantly to interface efficiency. That's why we use adaptive neural networks. This allows us to apply ‘smart’ search algorithms and determine mental equivalents of movements based on real-time electroencephalograms (EEG),” Dmitry Lazurenko, senior research scientist at the SFedU Research Center for Neurotechnology and Psychophysiology, explained.
Experts note that such systems are in high demand because they give a chance for successful rehabilitation and, most importantly, to awaken the independent activity of people with disabilities.
Laboratory of Neurotechnology and Psychophysiology of Southern Federal University (SFedU)
© Center for Public Communications of SFedU
As a result of the research, scientists have developed a software package that includes EEG processing methods that allows to understand exactly how the brain encodes information about movement.
“The advantage and novelty of our approach lies in the algorithm we developed, which allows us to determine the optimal settings of the brain signal classification method for solving the problem of neurocontrol and neurocommunication in the brain-computer interface loop,” Lazurenko said.
According to the SFedU’s leading research scientist, the conducted research constitutes a separate task of a major fundamental-applied project of the university. In future, the neurophysiological mechanisms of brain functioning under conditions of voluntary motor activity and free behavior will be studied simultaneously with the development of neurointerfaces for various purposes.
The research was carried out with the support of the Russian Science Foundation within the framework of the "Priority 2030" strategic academic leadership program. SFedU is a member of the federal program of the Ministry of Science and Higher Education of the Russian Federation on the "Research Leadership" track. The Southern Federal University’s development program includes five strategic projects, including the strategic project "Management Systems and Hybrid Intelligence”.
